1 | data_Y | data_X | |||
|---|---|---|---|---|---|
2 | 5.00 | 1 | |||
3 | 8.50 | 2.5 | |||
4 | 10.00 | 3.1 | |||
5 | 11.20 | 4 | |||
6 | 14.00 | 4.7 | |||
7 | 16.00 | 5.3 | |||
8 | 16.80 | 6 | |||
9 | 18.55 | 7.1 | |||
10 | 20.00 | 9 | |||
11 | |||||
12 | |||||
13 | Regression Coefficient | y-intercept | Formula | ||
14 | 1.997074937 | 3.863877797 | =LINEST(A2:A10, B2:B10, 1, 0) | ||
15 | |||||
16 | |||||
17 | All Statistics | Formula | |||
18 | 1.997074937 | 3.863877797 | =LINEST(A2:A10, B2:B10, 1, 1) | ||
19 | 0.1621557716 | 0.8554047831 | |||
20 | 0.9558856309 | 1.121834626 | |||
21 | 151.6784566 | 7 | |||
22 | 190.8892984 | 8.809590491 | |||
23 | |||||
24 | |||||
25 | Description | Statistic | |||
26 | The slope (gradient) of the line is | 1.997074937 | |||
27 | The y-intercept which is the value of y when x=0 is | 3.863877797 | |||
28 | The standard error value for the slope value is | 0.1621557716 | |||
29 | The standard error value for the y-intercept is | 0.8554047831 | |||
30 | The coefficient of determination is | 0.9558856309 | |||
31 | The standard error for the y estimate is | 1.121834626 | |||
32 | The F statistic is | 151.6784566 | |||
33 | The number of degrees of freedom is | 7 | |||
34 | The regression sum of squares is | 190.8892984 | |||
35 | The residual sum of squares is | 8.809590491 | |||
36 | |||||
1 | data_Y | data_X1 | data_X2 | |||
|---|---|---|---|---|---|---|
2 | 5.00 | 1 | 9 | |||
3 | 8.50 | 2.5 | 12 | |||
4 | 10.00 | 3.1 | 13 | |||
5 | 11.20 | 4 | 14 | |||
6 | 14.00 | 4.7 | 14.5 | |||
7 | 16.00 | 5.3 | 16 | |||
8 | 16.80 | 6 | 17 | |||
9 | 18.55 | 7.1 | 19 | |||
10 | 20.00 | 9 | 19.6 | |||
11 | ||||||
12 | ||||||
13 | Regression Coefficient | y-intercept | Formula | |||
14 | X2 | X1 | ||||
15 | 1.151703005 | 0.4252874858 | -5.839238736 | =LINEST(A2:A10,B2:C10, 1, 0) | ||
16 | ||||||
17 | ||||||
18 | All Statistics | Formula | ||||
19 | 1.151703005 | 0.4252874858 | -5.839238736 | =LINEST(A2:A10, B2:C10, 1, 1) | ||
20 | 0.4913762308 | 0.6824417895 | 4.193330885 | |||
21 | 0.9769708817 | 0.8754893237 | #N/A | |||
22 | 127.2698593 | 6 | #N/A | |||
23 | 195.0999996 | 4.598889335 | #N/A | |||
24 | ||||||
25 | ||||||
26 | Description | Statistic | ||||
27 | The values of the coefficients are | X2 | 1.151703005 | |||
28 | X1 | 0.4252874858 | ||||
29 | The y-intercept which is the value of y when x=0 is | -5.839238736 | ||||
30 | The standard error values for the coefficients are | X2 | 0.4913762308 | |||
31 | X1 | 0.6824417895 | ||||
32 | The standard error value for the y-intercept is | 4.193330885 | ||||
33 | The coefficient of determination is | 0.9769708817 | ||||
34 | The standard error for the y estimate is | 0.8754893237 | ||||
35 | The F statistic is | 127.2698593 | ||||
36 | The number of degrees of freedom is | 6 | ||||
37 | The regression sum of squares is | 195.0999996 | ||||
38 | The residual sum of squares is | 4.598889335 | ||||
39 | The unused cells display as | #N/A | ||||